ReviewJournal of structural biology2022
Deep generative modeling for volume reconstruction in cryo-electron microscopy.
Review in Journal of structural biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
26 citing papers in PubMed, 43 citations in OpenAlex.
- The CAHRA Challenge: A Community-Wide Assessment of Cryo-EM Heterogeneous Reconstruction Algorithms.bioRxiv : the preprint server for biology · 2026Article
- Article
- Statistical crystallography reveals an allosteric network in SARS-CoV-2 MCommunications biology · 2026Article
- Bayesian perspective for orientation determination in cryo-EM with application to structural heterogeneity analysis.Acta crystallographica. Section D, Structural biology · 2026Article
- CryoJAX: a cryo-electron microscopy image-simulation library in JAX.Acta crystallographica. Section D, Structural biology · 2026Article
- In Situ Liquid-Cell Transmission Electron Microscopy Insights Into Lithium-Ion Battery Materials Degradation: Challenges and Emerging Solutions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Stability and Inference of the Euler Characteristic Transform.Discrete & computational geometry · 2026Article
- Subspace Method of Moments forSIAM journal on imaging sciences · 2026Article
- The Inaugural Flatiron Institute Cryo-EM Conformational Heterogeneity Challenge.bioRxiv : the preprint server for biology · 2025Article
- cryoJAX: A Cryo-electron Microscopy Image Simulation Library In JAX.bioRxiv : the preprint server for biology · 2025Article
- Bayesian Perspective for Orientation Determination in Cryo-EM with Application to Structural Heterogeneity Analysis.bioRxiv : the preprint server for biology · 2025Article
- PERC: a suite of software tools for the curation of cryoEM data with application to simulation, modeling and machine learning.Acta crystallographica. Section F, Structural biology communications · 2025Article
- Amortized template matching of molecular conformations from cryoelectron microscopy images using simulation-based inference.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- InstaMap: instant-NGP for cryo-EM density maps.Acta crystallographica. Section D, Structural biology · 2025Article
- Cryo-EM heterogeneity analysis using regularized covariance estimation and kernel regression.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Structural Biology for Target Identification and Validation.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Cryo-EM Heterogeneity Analysis using Regularized Covariance Estimation and Kernel Regression.bioRxiv : the preprint server for biology · 2024Article
- Self Fourier shell correlation: properties and application to cryo-ET.Communications biology · 2024Article
- Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations.Frontiers in molecular biosciences · 2024Article
- Self Fourier shell correlation: properties and application to cryo-ET.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
Abstract
Advances in cryo-electron microscopy (cryo-EM) for high-resolution imaging of biomolecules in solution have provided new challenges and opportunities for algorithm development for 3D reconstruction. Next-generation volume reconstruction algorithms that combine generative modelling with end-to-end unsupervised deep learning techniques have shown promise, but many technical and theoretical hurdles remain, especially when applied to experimental cryo-EM images. In light of the proliferation of such methods, we propose here a critical review of recent advances in the field of deep generative modelling for cryo-EM reconstruction. The present review aims to (i) provide a unified statistical framework using terminology familiar to machine learning researchers with no specific background in cryo-EM, (ii) review the current methods in this framework, and (iii) outline outstanding bottlenecks and avenues for improvements in the field.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.